datawhalechina/competition-baseline

This repository collects baseline solutions for Chinese AI and data science competitions. A baseline is a working starting-point solution that shows one way to approach a contest problem. The goal is not to provide winning code but to give beginners a clear, readable example they can learn from and build on. The repository covers competitions in several areas: data mining, computer vision, natural language processing, and recommendation systems. Each competition folder contains code and notes explaining the approach. Competitions listed span several years and include events hosted by major Chinese technology companies and academic organizations, covering tasks like image classification, text matching, time-series forecasting, fraud detection, and deepfake detection. The primary audience is people new to data competitions who want to see how experienced practitioners set up a project, process data, train a model, and submit predictions. The README links to a competition calendar and related social media channels where new competition information and fresh baseline code are announced. All code samples are in Jupyter Notebooks, which let readers read explanations and run code side by side. A mirror of the repository is hosted inside China for faster access. The project is maintained by DataWhale China, a community focused on AI education and open collaboration. The full README is longer than what was shown.